Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Giovanni BARONE-ADESI"'
Publikováno v:
Journal of Econometrics. 216:430-449
We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision par
Autor:
Giovanni Barone-Adesi, Carlo Sala
Publikováno v:
Stochastic Analysis and Applications. 38:686-707
This paper provides a theoretical analysis on the impacts of using a suboptimal information set for the estimation of the pricing kernel and, more in general, for the validity of the fundamental th...
Publikováno v:
Annals of Operations Research. 313:603-604
Publikováno v:
International Journal of Finance & Economics. 24:1409-1428
The forward‐looking nature of option market data allows one to derive economically based and model‐free risk measures. This article proposes an extensive analysis of the performances of option‐implied value at risk and conditional value at risk
Autor:
Giovanni Barone-Adesi, Carlo Sala
Publikováno v:
The European Journal of Finance. 25:1166-1193
Market efficiency and the pricing kernel are closely related. A non-monotonic decreasing pricing kernel implies the existence of a trading strategy in contingent claims that stochastically ...
Publikováno v:
SSRN Electronic Journal.
Is it possible to achieve almost riskless, nonfluctuating investment payoffs in the long run, at a fraction of the traditional funding requirement, using equity investments? The persistence of low interest rates is spurring research on this question
Publikováno v:
The European Journal of Finance. 24:413-425
The estimation of joint tail risk is necessary to evaluate the size of portfolio margins and default funds of central counterparties. The ability of filtered historical simulation to satisfy new regulatory requirements in this area is examined at the
Publikováno v:
Journal of Forecasting.
Publikováno v:
SSRN Electronic Journal.
The problem of market predictability can be decomposed into two parts: predictive models and predictors. At first, we show how the joint employment of model selection and machine learning models can dramatically increase our capability to forecast th
Publikováno v:
SSRN Electronic Journal.
Empirical indicators of sentiment are commonly employed in the economic literature while a precise understanding of what is sentiment is still missing. Exploring the links among the most popular proxies of sentiment, fear and uncertainty this paper a